PhD Studentship

Geographic Information Systems (GIS) have seen a major shift thanks to recent strides in aerial and satellite data technologies, covering acquisition, sharing, and interpretation. However, challenges in data quality and compatibility persist, necessitating manual corrections that are both time-consuming and limit scalability. Despite the availability of...

Geographic Information Systems (GIS) have seen a major shift thanks to recent strides in aerial and satellite data technologies, covering acquisition, sharing, and interpretation. However, challenges in data quality and compatibility persist, necessitating manual corrections that are both time-consuming and limit scalability. Despite the availability of...

Geographic Information Systems (GIS) have seen a major shift thanks to recent strides in aerial and satellite data technologies, covering acquisition, sharing, and interpretation. However, challenges in data quality and compatibility persist, necessitating manual corrections that are both time-consuming and limit scalability. Despite the availability of...

Recent years have witnessed significant strides made by machine learning-based computer vision, thus enabling machines to interpret and understand visual information. However, most machine learning approaches exploit correlational relationships in a training data set to predict a target variable. When these correlations are spurious or unreliable, those...

Recent years have witnessed significant strides made by machine learning-based computer vision, thus enabling machines to interpret and understand visual information. However, most machine learning approaches exploit correlational relationships in a training data set to predict a target variable. When these correlations are spurious or unreliable, those...

Recent years have witnessed significant strides made by machine learning-based computer vision, thus enabling machines to interpret and understand visual information. However, most machine learning approaches exploit correlational relationships in a training data set to predict a target variable. When these correlations are spurious or unreliable, those...

About the ProjectDecisions on adopting vaccine policies for infectious diseases can be informed by model-based economic evaluations of the costs and benefits achieved, including the indirect benefits by reducing transmission. Supply-chain and manufacturing process design can also be informed by modelling. Additional investments in manufacturing processes may...

We have a vacancy for an enthusiastic and self-motivated PhD student for a PhD project in the Leonardo Centre at the University of Sheffield funded by the John Crane Ltd.About the ProjectThe transition away from fossil fuels has been rapid. Increasingly our energy comes from renewable sources such as wind and solar. These sources are intermittent which means...

We have a vacancy for an enthusiastic and self-motivated PhD student for a PhD project in the Leonardo Centre at the University of Sheffield funded by the John Crane Ltd.About the ProjectThe transition away from fossil fuels has been rapid. Increasingly our energy comes from renewable sources such as wind and solar. These sources are intermittent which means...

Anti-ferromagnets are emerging as key materials for a variety of modern technologies across data storage, processing and more. Recent advances have demonstrated how they can be efficiently manipulated at high frequency but at this scale the interaction of the magnetisation with the atomic structure is important. This project will explore the complex dynamics...

Anti-ferromagnets are emerging as key materials for a variety of modern technologies across data storage, processing and more. Recent advances have demonstrated how they can be efficiently manipulated at high frequency but at this scale the interaction of the magnetisation with the atomic structure is important. This project will explore the complex dynamics...

Artificial intelligence (AI) applications are transformative, but they are becoming increasingly unsustainable. Many AI models require extensive training with large model sizes. As an alternative reservoir computing exploits random fixed networks to transform data to simplify training. By creating structure within these networks, much like the natural...

Artificial intelligence (AI) applications are transformative, but they are becoming increasingly unsustainable. Many AI models require extensive training with large model sizes. As an alternative reservoir computing exploits random fixed networks to transform data to simplify training. By creating structure within these networks, much like the natural...

Neuromorphic devices aim to emulate the structure of the human brain to develop resource efficient computing systems. Recent developments have shown strong growth but the complexity of manufacturing many operating elements is challenging to scale indefinitely. To circumvent this, we aim to use bespoke nanoscale devices as 'complex' neurons that operate as...

Neuromorphic devices aim to emulate the structure of the human brain to develop resource efficient computing systems. Recent developments have shown strong growth but the complexity of manufacturing many operating elements is challenging to scale indefinitely. To circumvent this, we aim to use bespoke nanoscale devices as 'complex' neurons that operate as...

Do you want to pioneer using cutting edge technology to investigate how work-related interactions are impacting employees' loneliness? This fully funded PhD offers access to a vibrant research community within the Institute of Work Psychology and an opportunity to collaborate with experts from the University of Canterbury in New Zealand.The overarching aim...

Do you want to pioneer using cutting edge technology to investigate how work-related interactions are impacting employees' loneliness? This fully funded PhD offers access to a vibrant research community within the Institute of Work Psychology and an opportunity to collaborate with experts from the University of Canterbury in New Zealand.The overarching aim...

This PhD project will use two secondary datasets and a series of experiments to explore how teams led by white women and ethnic minorities manage status related conflict in newly formed teams. The project will draw on Expectation States Theory which highlights how individuals in newly formed performance-oriented groups are likely to be granted high and low...

This PhD project will use two secondary datasets and a series of experiments to explore how teams led by white women and ethnic minorities manage status related conflict in newly formed teams. The project will draw on Expectation States Theory which highlights how individuals in newly formed performance-oriented groups are likely to be granted high and low...

This PhD project will use two secondary datasets and a series of experiments to explore how teams led by white women and ethnic minorities manage status related conflict in newly formed teams. The project will draw on Expectation States Theory which highlights how individuals in newly formed performance-oriented groups are likely to be granted high and low...